The proposed study will utilize 1781 addict career histories (1441 males and 337 females) accumulated from four long-term followup studies of chronic addicts identified from admissions to the California Civil Addict Program and various Southern California methadone maintenance treatment programs. The comprehensive data base includes self-reported demographics, family characteristics, academic background, and non-narcotic drug use history. Retrospective longitudinal interviews covering a period from 12 months prior to first narcotic use to interview provide behavioral data about narcotics use, legal supervision status, crime involvement, drug trafficking, employment, marital status, and treatment involvement. Corroborative data was obtained from the official arrest and methadone maintenance treatment records for each subject and from a volunteer urine specimen taken at interview. Data manipulation computer programs have been developed in the earlier studies which convert the data to a form suitable for statistical analysis. Planned analyses include: (1a) an analysis of the general relationship between narcotic use and crime; (b) how the drug/crime relationship varied across race and sex; (c) causal modeling (LISREL) of the drugs/crime relationship in the context of a general deviance model; (2) sex differences in the initiation, maintenance, and cessation of addiction; (3) interpersonal influence in addict couples; (4) time series analysis techniques applied to drug abuse research data; (5) alcohol and non-narcotic drug abuse problems of heroin addicts; and (6) causal modeling of treatment effects on addiction and crime. (These analyses are detailed in Appendix B.) Proposed analyses include: 1) discriminant analysis differentiating those amenable to compulsory treatment approaches from those who are not; 2) a similar analysis for those responding to methadone maintenance treatment from those who do not; 3) an evaluation of the effectiveness of legal supervision in suppressing drug use and associated crime; 4a) determining predictors of those maturing out of addiction by time of interview from those who do not, b) developing a causal model describing the relationship between such predictors; 5) an economic assessment of addict sources of income while addicted and while not addicted; 6a) a categorization of addict typologies using cluster analysis of continuous variables or factor analysis of polytomous variables and, b) a relating of such typologies to outcome for different treatment modalities.